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Author Sándor, R.; Barcza, Z.; Hidy, D.; Lellei-Kovács, E.; Ma, S.; Bellocchi, G.
Title Modelling of grassland fluxes in Europe: evaluation of two biogeochemical models Type Journal Article
Year 2016 Publication Agriculture, Ecosystems and Environment Abbreviated Journal Agric. Ecosyst. Environ.
Volume 215 Issue Pages 1-19
Keywords carbon-water fluxes; climate change; grasslands; model comparison; net ecosystem exchange; terrestrial carbon balance; pasture simulation-model; climate-change; nitrous-oxide; land-use; co2; photosynthesis; responses; water
Abstract (up) Two independently developed simulation models – the grassland-specific PaSim and the biome-generic Biome-BGC MuSo (BBGC MuSo) – linking climate, soil, vegetation and management to ecosystem biogeochemical cycles were compared in a simulation of carbon (C) and water fluxes. The results were assessed against eddy-covariance flux data from five observational grassland sites representing a range of conditions in Europe: Grillenburg in Germany, Laqueuille in France with both extensive and intensive management, Monte Bondone in Italy and Oensingen in Switzerland. Model comparison (after calibration) gave substantial agreement, the performances being marginal to acceptable for weekly-aggregated gross primary production and ecosystem respiration (R-2 similar to 0.66 – 0.91), weekly evapotranspiration (R-2 similar to 0.78 – 0.94), soil water content in the topsoil (R-2 similar to 0.1 -0.7) and soil temperature (R-2 similar to 0.88 – 0.96). The bias was limited to the range -13 to 9 g C m(-2) week(-1) for C fluxes (-11 to 8 g C m(-2) week(-1) in case of BBGC MuSo, and -13 to 9 g C m(-2) week(-1) in case of PaSim) and -4 to 6 mm week for water fluxes (with BBGC MuSo providing somewhat higher estimates than PaSim), but some higher relative root mean square errors indicate low accuracy for prediction, especially for net ecosystem exchange The sensitivity of simulated outputs to changes in atmospheric carbon dioxide concentration ([CO2]), temperature and precipitation indicate, with certain agreement between the two models, that C outcomes are dominated by [CO2] and temperature gradients, and are less due to precipitation. ET rates decrease with increasing [CO2] in PaSim (consistent with experimental knowledge), while lack of appropriate stomatal response could be a limit in BBGC MuSo responsiveness. Results of the study indicate that some of the errors might be related to the improper representation of soil water content and soil temperature. Improvement is needed in the model representations of soil processes (especially soil water balance) that strongly influence the biogeochemical cycles of managed and unmanaged grasslands. (C) 2015 Elsevier B.V. All rights reserved.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0167-8809 ISBN Medium Article
Area Expedition Conference
Notes CropM, LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4808
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Author Valin, H.; Sands, R.D.; van der Mensbrugghe, D. and; Nelson, G.C.; Ahammad, H.; Blanc, E.; Bodirsky; Benjamin; Fujimori, S.; Hasegawa, T.; Havlik, P.; and Heyhoe, E.; Kyle, P.; Mason-D’Croz, D.; Paltsev; Sergey; Rolinski, S.; Tabeau, A.; van Meijl, H. and; von Lampe, M.; Willenbockel, D.
Title The future of food demand: Understanding differences in global economic models Type Journal Article
Year 2014 Publication Agricultural Economics Abbreviated Journal Agric. Econ.
Volume 45 Issue 1 Pages 51-67
Keywords world food demand; socioeconomic pathways; climate change; computable general equilibrium; partial equilibrium; systems
Abstract (up) Understanding the capacity of agricultural systems to feed the world population under climate change requires projecting future food demand. This article reviews demand modeling approaches from 10 global economic models participating in the Agricultural Model Intercomparison and Improvement Project (AgMIP). We compare food demand projections in 2050 for various regions and agricultural products under harmonized scenarios of socioeconomic development, climate change, and bioenergy expansion. In the reference scenario (SSP2), food demand increases by 59-98% between 2005 and 2050, slightly higher than the most recent FAO projection of 54% from 2005/2007. The range of results is large, in particular for animal calories (between 61% and 144%), caused by differences in demand systems specifications, and in income and price elasticities. The results are more sensitive to socioeconomic assumptions than to climate change or bioenergy scenarios. When considering a world with higher population and lower economic growth (SSP3), consumption per capita drops on average by 9\% for crops and 18% for livestock. The maximum effect of climate change on calorie availability is -6% at the global level, and the effect of biofuel production on calorie availability is even smaller.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0169-5150 ISBN Medium Article
Area Expedition Conference
Notes TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4752
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Author Lardy, R.; Bellocchi, G.; Martin, R.
Title Vuln-Indices: Software to assess vulnerability to climate change Type Journal Article
Year 2015 Publication Computers and Electronics in Agriculture Abbreviated Journal Computers and Electronics in Agriculture
Volume 114 Issue Pages 53-57
Keywords climate change; Java; vulnerability indices; pasture simulation-model; integrated assessment; environmental-change; change impacts; system
Abstract (up) Vuln-Indices Java-based software was developed on concepts of vulnerability to climate change of agro-ecological systems. It implements the calculation of vulnerability indices on series of state variables for assessments at both site and region levels. The tool is useful because synthetic indices help capturing complex processes and prove effective to identify the factors responsible for vulnerability and their relative importance. It is suggested that the tool may be plausible for use with stakeholders to disseminate information of climate change impacts. (C) 2015 Elsevier B.V. All rights reserved.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-1699 ISBN Medium Article
Area Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4648
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Author Zhao, G.; Hoffmann, H.; van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.L.; Constantin, J.; Raynal, H.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.G.; Nendel, C.; Kiese, R.; Eckersten, H.; Haas, E.; Vanuytrecht, E.; Wang, E.; Kuhnert, M.; Trombi, G.; Moriondo, M.; Bindi, M.; Lewan, E.; Bach, M.; Kersebaum, K.C.; Rotter, R.; Roggero, P.P.; Wallach, D.; Cammarano, D.; Asseng, S.; Krauss, G.; Siebert, S.; Gaiser, T.; Ewert, F.
Title Effect of weather data aggregation on regional crop simulation for different crops, production conditions, and response variables Type Journal Article
Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.
Volume 65 Issue Pages 141-157
Keywords crop model; model comparison; spatial resolution; data aggregation; spatial heterogeneity; scaling; climate-change scenarios; sub-saharan africa; winter-wheat; spatial-resolution; yield response; input data; systems simulation; large-scale; soil data; part i
Abstract (up) We assessed the weather data aggregation effect (DAE) on the simulation of cropping systems for different crops, response variables, and production conditions. Using 13 process-based crop models and the ensemble mean, we simulated 30 yr continuous cropping systems for 2 crops (winter wheat and silage maize) under 3 production conditions for the state of North Rhine-Westphalia, Germany. The DAE was evaluated for 5 weather data resolutions (i.e. 1, 10, 25, 50, and 100 km) for 3 response variables including yield, growing season evapotranspiration, and water use efficiency. Five metrics, viz. the spatial bias (Delta), average absolute deviation (AAD), relative AAD, root mean squared error (RMSE), and relative RMSE, were used to evaluate the DAE on both the input weather data and simulated results. For weather data, we found that data aggregation narrowed the spatial variability but widened the., especially across mountainous areas. The DAE on loss of spatial heterogeneity and hotspots was stronger than on the average changes over the region. The DAE increased when coarsening the spatial resolution of the input weather data. The DAE varied considerably across different models, but changed only slightly for different production conditions and crops. We conclude that if spatially detailed information is essential for local management decision, higher resolution is desirable to adequately capture the spatial variability for heterogeneous regions. The required resolution depends on the choice of the model as well as the environmental condition of the study area.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0936-577x ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4754
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Author Ruane, A.C.; Hudson, N.I.; Asseng, S.; Camarrano, D.; Ewert, F.; Martre, P.; Boote, K.J.; Thorburn, P.J.; Aggarwal, P.K.; Angulo, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Brisson, N.; Challinor, &rew J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.F.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Kumar, S.N.; Müller, C.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Rötter, R.P.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Wolf, J.
Title Multi-wheat-model ensemble responses to interannual climate variability Type Journal Article
Year 2016 Publication Environmental Modelling & Software Abbreviated Journal Env. Model. Softw.
Volume 81 Issue Pages 86-101
Keywords Crop modeling; Uncertainty; Multi-model ensemble; Wheat; AgMIP; Climate; impacts; Temperature; Precipitation; lnterannual variability; simulation-model; crop model; nitrogen dynamics; winter-wheat; large-area; systems simulation; farming systems; yield response; growth; water
Abstract (up) We compare 27 wheat models’ yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981-2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models’ climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R-2 <= 0.24) was found between the models’ sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts. Published by Elsevier Ltd.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1364-8152 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4769
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